Who Should Stop Unethical A.I.?

In computer science, the main outlets for peer-reviewed research are not journals but conferences, where accepted papers are presented in the form of talks or posters. In June, 2019, at a large artificial-intelligence conference in Long Beach, California, called Computer Vision and Pattern Recognition, I stopped to look at a poster for a project called Speech2Face. Using machine learning, researchers had developed an algorithm that generated images of faces from recordings of speech. A neat idea, I thought, but one with unimpressive results: at best, the faces matched the speakers' sex, age, and ethnicity--attributes that a casual listener might guess. That December, I saw a similar poster at another large A.I. conference, Neural Information Processing Systems (NeurIPS), in Vancouver, Canada.